Methods of the second type work in a variety of different ways and can be considered a category of exclusion. For example, Deep Image Prior (DIP) [1]} attempts to exploit the innate structure of a convolutional neural network to recover the image from random inputs. Another example is Noise2Fast (N2F) [2]} which attempts to learn to denoise the image from its downsamplings. In general, these denoisers learn to denoise the image quickly, but they require convergence criteria to avoid overfitting.
